This paper aims to achieve vibration suppression for multi-component floating structures under ocean waves. To this end, a multiple-passive-TMD (tuned mass damper) structure is employed, and numerical model developed incorporating both the dynamics of hinged foundation passive TMDs. A data-driven parameter optimization method search optimal TMD parameters. built upon Bayesian Ascent (BA) – an a...

In this study, two variants of genetic programming, namely linear genetic programming (LGP) and multi-expression programming (MEP) are utilized to detect atrial fibrillation (AF) episodes. LGPand MEP-based models are derived to classify samples of AF and Normal episodes based on the analysis of RR interval signals. A weighted least-squares (WLS) regression analysis is performed using the same f...

This article presents a language-independent emotion recognition system for the identification of human affective state in the speech signal. A group of potential features are first identified and extracted to represent the characteristics of different emotions. To reduce the dimensionality of the feature space, whilst increasing the discriminatory power of the features, we introduce a systemat...

A major characteristic of text document classification problem is extremely high dimensionality of text data. In this paper we present two algorithms for feature (word) selection for the purpose of text classification. We used sequential forward selection methods based on improved mutual information introduced by Battiti [1] and Kwak and Choi [6] for non-textual data. These feature evaluation f...

This paper proposes a genetic algorithm feature selection (GAFS) for image retrieval systems and image classification. Two texture features of adaptive motifs co-occurrence matrix (AMCOM) and gradient histogram for adaptive motifs (GHAM) and color feature of an adaptive color histogram for K-means (ACH) were used in this paper. In this paper, the feature selections have adopted sequential forwa...

Sequential forward selection (SFS) is one of the most widely used feature selection procedures. It starts with an empty set and adds one feature at each step. The estimate of the quality of the candidate subsets usually depends on the training/testing split of the data. Therefore different sequences of features may be returned from repeated runs of SFS. A substantial discrepancy between such se...

Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this is...

The offshore wind sector is expanding to deep water locations through floating platforms. This poses challenges horizontal axis turbines (HAWTs) due the ever growing size of blades and support structures. As such, maintaining structural integrity reducing levelised cost energy (LCoE) HAWTs seems increasingly difficult. An alternative these could be found in vertical (VAWTs). It known that VAWTs...

In this paper, a novel method to recognize stem or calyx regions of ‘Jonagold’ apples by pattern recognition is proposed. The method starts with background removal and object segmentation by thresholding. Statistical, textural and shape features are extracted from each segmented object and these features are introduced to several supervised classification algorithms. Linear discriminant, neares...

Floating point units form an important component of many reconfigurable computing applications. The creation of floating point units under a collection of area, latency, and throughput constraints is an important consideration for system designers. Given the range of possible tradeoffs, most commercial or academic floating point libraries for FPGAs provide a small fraction of possible floating ...